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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20260522T150111Z
LOCATION:C2/3/4 Ballroom
DTSTART;TZID=America/Chicago:20181115T083000
DTEND;TZID=America/Chicago:20181115T170000
UID:submissions.supercomputing.org_SC18_sess324_post206@linklings.com
SUMMARY:Interactive HPC Deep Learning with Jupyter Notebooks
DESCRIPTION:Wahid Bhimji, Steven Farrell, Oliver Evans, Matthew Henderson,
  and Shreyas Cholia (Lawrence Berkeley National Laboratory); Aaron Vose (C
 ray Inc); and Mr Prabhat, Rollin Thomas, and Richard Shane Canon (Lawrence
  Berkeley National Laboratory)\n\nDeep learning researchers are increasing
 ly using Jupyter notebooks to implement interactive, reproducible workflow
 s. Such solutions are typically deployed on small-scale (e.g. single serve
 r) computing systems. However, as the sizes and complexities of datasets a
 nd associated neural network models increase, distributed systems become i
 mportant for training and evaluating models in a feasible amount of time. 
 In this poster, we describe our work on Jupyter notebook solutions for dis
 tributed training and hyper-parameter optimization of deep neural networks
  on high-performance computing systems.\n\nRegistration Category: Tech Pro
 gram Reg Pass, Exhibits Reg Pass\n\n
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